A novel Multi-permittivity Cylindrical Dielectric Resonator Antenna for Wideband Applications

In this paper, a novel multi-permittivity cylindrical dielectric resonator antenna for wideband application is presented. The multi-permittivity cylinder is formed by combining two different permittivity material sectors in such a way that each sector (with constant permittivity) is 90 degree apart. A direct microstrip line coupling terminated with T-stub at the open end is used to excite the multi-permittivity cylindrical dielectric resonator. The angular position of the multi sector dielectric resonator with respect to the longitudinal axis of the microstrip line and length of the additional strip at the open end of the feeding circuit is key parameters for wideband operation of the antenna. By optimizing all parameters of the proposed antenna, wideband impedance bandwidth of 56% (12.1 GHz - 21.65 GHz) is achieved. The average gain of the antenna throughout the bandwidth is 5.9 dB with good radiation properties in both E-plane and H-plane. A well matched simulation and experimental results show that the antenna is suitable for wideband applications

IMPLEMENTATION OF NEURAL - CRYPTOGRAPHIC SYSTEM USING FPGA

Modern cryptography techniques are virtually unbreakable. As the Internet and other forms of electronic communication become more prevalent, electronic security is becoming increasingly important. Cryptography is used to protect e-mail messages, credit card information, and corporate data. The design of the cryptography system is a conventional cryptography that uses one key for encryption and decryption process. The chosen cryptography algorithm is stream cipher algorithm that encrypt one bit at a time. The central problem in the stream-cipher cryptography is the difficulty of generating a long unpredictable sequence of binary signals from short and random key. Pseudo random number generators (PRNG) have been widely used to construct this key sequence. The pseudo random number generator was designed using the Artificial Neural Networks (ANN). The Artificial Neural Networks (ANN) providing the required nonlinearity properties that increases the randomness statistical properties of the pseudo random generator. The learning algorithm of this neural network is backpropagation learning algorithm. The learning process was done by software program in Matlab (software implementation) to get the efficient weights. Then, the learned neural network was implemented using field programmable gate array (FPGA)

Design Minkowski Shaped Patch Antenna with Rectangular Parasitic Patch Elements for 5.8 GHz Applications

Abstract—This paper presents the parametric study on the Minkowski shaped antenna with the rectangular parasitic patch elements. This patch antenna consists four parts – patch, feed line, ground plane and parasitic elements. The rectangular parasitic patch elements are located at the bottom of the Minkowski shaped patch. The parametric study of different patch sizes (Design 2A, Design 2B, Design 2C, Design 2D and Design 2E) is presented in this paper. The antenna parameters studied in this paper are resonant frequencies, return loss at the resonant frequency, bandwidth and realized gain. The target frequency of this antenna is 5.80 GHz for Worldwide Interoperability for Microwave Access (WiMAX) application. It shows the return loss of – 24.477 dB, bandwidth of 254 MHz (5.676 GHz to 5.930 GHz) and a gain of 2.351 dB. Index Terms—Minkowski; patch antenna; gain; return loss; bandwidt

Wireless Hybrid Vehicle Three-Phase Motor Diagnosis Using Z-Freq Due to Unbalance Fault

Online diagnostics of three phase motor rotor faults of hybrid vehicle can be identified using a method called machine learning. Unfortunately, there is still a constraint in achieving a high success rate because a huge volume of training data is required. These faults were represented on its frequency content throughout the Fast Fourier Transform (FFT) algorithm to observe data acquired from multi-signal sensors. At that point, these failure-induced faults studies were improved using an enhanced statistical frequency-based analysis named Z-freq to optimize the study. This analysis is an investigation of the frequency domain of data acquired from the turbine blade after it runs under a specific condition. During the experiment, the faults were simulated by equipment with all those four conditions including normal mode. The failure induced by fault signals from static, coupled and dynamic were measured using high sensitivity, space-saving and a durable piezo-based sensor called a wireless accelerometer. The obtained result and analysis showed a significant pattern in the coefficient value and distribution of Z-freq data scattered for all flaws. Finally, the simulation and experimental output were verified and validated in a series of performance metrics tests using accuracy, sensitivity, and specificity for prediction purposes. This outcome has a great prospect to diagnose and monitor hybrid electric motor wirelessly. &nbsp

Wireless Hybrid Vehicle Three-Phase Motor Diagnosis Using Z-Freq Due to Unbalance Fault

Online diagnostics of three phase motor rotor faults of hybrid vehicle can be identified using a method called machine learning. Unfortunately, there is still a constraint in achieving a high success rate because a huge volume of training data is required. These faults were represented on its frequency content throughout the Fast Fourier Transform (FFT) algorithm to observe data acquired from multi-signal sensors. At that point, these failure-induced faults studies were improved using an enhanced statistical frequency-based analysis named Z-freq to optimize the study. This analysis is an investigation of the frequency domain of data acquired from the turbine blade after it runs under a specific condition. During the experiment, the faults were simulated by equipment with all those four conditions including normal mode. The failure induced by fault signals from static, coupled and dynamic were measured using high sensitivity, space-saving and a durable piezo-based sensor called a wireless accelerometer. The obtained result and analysis showed a significant pattern in the coefficient value and distribution of Z-freq data scattered for all flaws. Finally, the simulation and experimental output were verified and validated in a series of performance metrics tests using accuracy, sensitivity, and specificity for prediction purposes. This outcome has a great prospect to diagnose and monitor hybrid electric motor wirelessly. &nbsp

Comparison Study On Pinch-Hitting Vibration Signal Analysis for Automotive Bearing: I-KazTM and I-Kaz 3D

Rotating machines are now an essential part of the automotive industry. Meanwhile, a bearing is playing the most important component of rotating machinery. To sustain the system's smooth running, maintenance methods such as preventive maintenance, breakdown maintenance, and predictive maintenance are used. Under preventive maintenance, vibration analysis is used to diagnose machines bearing faults. The main objective is to recognize bearing defects in a mechanical device by acquiring signals from the bearing using data acquisition hardware. This analysis is conducted under various load torque conditions, speeds, and defect types. A modular hardware configuration consisting of an accelerometer acquires the vibration signal. The signals are analyzed by using I-kazTM and I-kaz 3D signal analysis and its main objective is to observe the degree of dispersion data from its mean point.  This analysis resolves the issues associated with time domain analysis. This pinch-hitting analysis research was conducted in two stages.  The first stage is an experimental process that uses 3 types of bearings, the healthy (BL), inner race fault (IRF), and defect at outer race (ORF) bearing on the Machine Fault Simulator and forces with a different type of speed (1000, 1500 and 2500 rpm) and load variation (0.0564, 0.564 and 1.1298 N-m). In the second stage, computing the coefficient value and plots of signal’s I-kazTM and I-kaz 3D based on the bearings type were done accordingly. As a result, the analysis for detecting inner race fault, the deviation percentage averages calculation obtained the I-kazTM coefficient shows a better result with 96.86% by comparing to the I-kaz 3D that achieves 94.20%. Similarly, for the outer race defect, I-kazTM lead with 65.40% compared to I-kaz 3D with only 54.82%.  &nbsp

Comparison Study On Pinch-Hitting Vibration Signal Analysis for Automotive Bearing: I-KazTM and I-Kaz 3D

Rotating machines are now an essential part of the automotive industry. Meanwhile, a bearing is playing the most important component of rotating machinery. To sustain the system's smooth running, maintenance methods such as preventive maintenance, breakdown maintenance, and predictive maintenance are used. Under preventive maintenance, vibration analysis is used to diagnose machines bearing faults. The main objective is to recognize bearing defects in a mechanical device by acquiring signals from the bearing using data acquisition hardware. This analysis is conducted under various load torque conditions, speeds, and defect types. A modular hardware configuration consisting of an accelerometer acquires the vibration signal. The signals are analyzed by using I-kazTM and I-kaz 3D signal analysis and its main objective is to observe the degree of dispersion data from its mean point.  This analysis resolves the issues associated with time domain analysis. This pinch-hitting analysis research was conducted in two stages.  The first stage is an experimental process that uses 3 types of bearings, the healthy (BL), inner race fault (IRF), and defect at outer race (ORF) bearing on the Machine Fault Simulator and forces with a different type of speed (1000, 1500 and 2500 rpm) and load variation (0.0564, 0.564 and 1.1298 N-m). In the second stage, computing the coefficient value and plots of signal’s I-kazTM and I-kaz 3D based on the bearings type were done accordingly. As a result, the analysis for detecting inner race fault, the deviation percentage averages calculation obtained the I-kazTM coefficient shows a better result with 96.86% by comparing to the I-kaz 3D that achieves 94.20%. Similarly, for the outer race defect, I-kazTM lead with 65.40% compared to I-kaz 3D with only 54.82%.  &nbsp

Understanding media literacy in relation to adolescent soft drink consumption behavior

This paper examines relationship between media literacy and the Theory of Planned Behavior (TPB) variables focusing on consumption of soft drink among adolescents in Klang Valley, Malaysia. In addition, this paper also determines soft drink consumption, level of media literacy and the influences of the TPB variables on the intention of soft drink consumption. A cluster sampling method was used in collecting data within the Klang Valley area. The sample consisted of 436 adolescents from secondary school, aged between 13 to 18 years old. Two main scales utilized were Media Literacy (ML) scale and TPB scale. The descriptive, multiple linear regression and Pearson product-moment correlation analyses were carried out to answer the research objectives. Results revealed that 36% of respondents drank a minimum of 1 can, bottle or glass of soft drink for the past seven days and possess good level of media literacy (35%).Meanwhile, 14% of variance in adolescents’ intention of soft drink consumption is explained by TPB variables. Additionally, the total media literacy score towards soft drink advertisement was significantly positively correlated with attitude (r = 0.250, p<.05) and subjective norms (r = 0.174, p<.05). Conversely, total media literacy was significant negatively correlated with intention to consume soft drink (r = -0.19, p<.05) and indicated that media literacy could lower the intention to consume soft drink, thus can reduce soft drink consumption among adolescents. The importance of this study is to help the authorities, soft drink marketers and producers in Malaysia to better understand media literacy and adolescent soft drink consumption behavior

Feasibility Study on IPMC Actuated Contractile Water Jet Thruster Body Contraction

This research was conducted to investigate the feasibility of Ionic Polymer Metal Composite (IPMC) as the actuator for Contractile Water Jet Thruster (CWJT). The thrust that generated from the accelerated volume of ejected fluid depends on the IPMC actuator contraction performance. During this investigation, the variation of contraction frequency and nozzle aperture influence on the body deformation was carried out. The results of the experiments exhibit that the body contraction decreased tremendously from 0.05 Hz to 0.15 Hz. The body contraction has no apparent decrement for more than 0.15 Hz of contraction frequency. Besides, larger nozzle aperture has relatively more body contraction than smaller nozzle aperture. These results show that the fixed actuation force and the contraction frequency have a significant influence on the CWJT body contraction